The distribution of antibiotic use and its association with antibiotic resistance

  1. Scott W Olesen
  2. Michael L Barnett
  3. Derek R MacFadden
  4. John S Brownstein
  5. Sonia Hernández-Diaz
  6. Marc Lipsitch
  7. Yonatan H Grad  Is a corresponding author
  1. Harvard TH Chan School of Public Health, United States
  2. University of Toronto, Canada
  3. Boston Children's Hospital, United States

Abstract

Antibiotic use is a primary driver of antibiotic resistance. However, antibiotic use can be distributed in different ways in a population, and the association between the distribution of use and antibiotic resistance has not been explored. Here we tested the hypothesis that repeated use of antibiotics has a stronger association with population-wide antibiotic resistance than broadly-distributed, low-intensity use. First, we characterized the distribution of outpatient antibiotic use across US states, finding that antibiotic use is uneven and that repeated use of antibiotics makes up a minority of antibiotic use. Second, we compared antibiotic use with resistance for 72 pathogen-antibiotic combinations across states. Finally, having partitioned total use into extensive and intensive margins, we found that intense use had a weaker association with resistance than extensive use. If the use-resistance relationship is causal, these results suggest that reducing total use and selection intensity will require reducing broadly-distributed, low-intensity use.

Data availability

State-level, aggregate antibiotic use and resistance data used in the main analyses are in Figure 3 - Source data 1 and 2. We do not own and cannot publish disaggregated MarketScan or Medicare data. MarketScan data are available by commercial license from Truven Health (marketscan.truvenhealth.com). Medicare data are available from ResDAC (www.resdac.org). ResDAC requires an application ensuring that requesting researchers comply with Common Rule, HIPAA, and CMS security and privacy requirements. Disaggregated ResistanceOpen data are restricted due to hospitals' privacy concerns. ResistanceOpen data are available by request from HealthMap (www.resistanceopen.org).

Article and author information

Author details

  1. Scott W Olesen

    Department of Immunology and Infectious Diseases, Harvard TH Chan School of Public Health, Boston, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5400-4945
  2. Michael L Barnett

    Department of Health Policy and Management, Harvard TH Chan School of Public Health, Boston, United States
    Competing interests
    No competing interests declared.
  3. Derek R MacFadden

    Division of Infectious Diseases, Department of Medicine, University of Toronto, Toronto, Canada
    Competing interests
    No competing interests declared.
  4. John S Brownstein

    Boston Children's Hospital, Boston, United States
    Competing interests
    No competing interests declared.
  5. Sonia Hernández-Diaz

    Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, United States
    Competing interests
    No competing interests declared.
  6. Marc Lipsitch

    Department of Immunology and Infectious Diseases, Harvard TH Chan School of Public Health, Boston, United States
    Competing interests
    Marc Lipsitch, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1504-9213
  7. Yonatan H Grad

    Department of Immunology and Infectious Diseases, Harvard TH Chan School of Public Health, Boston, United States
    For correspondence
    ygrad@hsph.harvard.edu
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5646-1314

Funding

National Institute of General Medical Sciences (U54GM088558)

  • Scott W Olesen
  • Marc Lipsitch

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Neil M Ferguson, Imperial College London, United Kingdom

Version history

  1. Received: June 26, 2018
  2. Accepted: December 8, 2018
  3. Accepted Manuscript published: December 18, 2018 (version 1)
  4. Version of Record published: December 27, 2018 (version 2)

Copyright

© 2018, Olesen et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Scott W Olesen
  2. Michael L Barnett
  3. Derek R MacFadden
  4. John S Brownstein
  5. Sonia Hernández-Diaz
  6. Marc Lipsitch
  7. Yonatan H Grad
(2018)
The distribution of antibiotic use and its association with antibiotic resistance
eLife 7:e39435.
https://doi.org/10.7554/eLife.39435

Share this article

https://doi.org/10.7554/eLife.39435

Further reading

    1. Epidemiology and Global Health
    2. Microbiology and Infectious Disease
    Scott W Olesen, Marc Lipsitch, Yonatan H Grad

    We are writing to reply to the comment by Pouwels et al., 2019 about our recent study (Olesen et al., 2018) on antibiotic use and antibiotic resistance.

    1. Epidemiology and Global Health
    Sean V Connelly, Nicholas F Brazeau ... Jeffrey A Bailey
    Research Article

    Background:

    The Zanzibar archipelago of Tanzania has become a low-transmission area for Plasmodium falciparum. Despite being considered an area of pre-elimination for years, achieving elimination has been difficult, likely due to a combination of imported infections from mainland Tanzania and continued local transmission.

    Methods:

    To shed light on these sources of transmission, we applied highly multiplexed genotyping utilizing molecular inversion probes to characterize the genetic relatedness of 282 P. falciparum isolates collected across Zanzibar and in Bagamoyo district on the coastal mainland from 2016 to 2018.

    Results:

    Overall, parasite populations on the coastal mainland and Zanzibar archipelago remain highly related. However, parasite isolates from Zanzibar exhibit population microstructure due to the rapid decay of parasite relatedness over very short distances. This, along with highly related pairs within shehias, suggests ongoing low-level local transmission. We also identified highly related parasites across shehias that reflect human mobility on the main island of Unguja and identified a cluster of highly related parasites, suggestive of an outbreak, in the Micheweni district on Pemba island. Parasites in asymptomatic infections demonstrated higher complexity of infection than those in symptomatic infections, but have similar core genomes.

    Conclusions:

    Our data support importation as a main source of genetic diversity and contribution to the parasite population in Zanzibar, but they also show local outbreak clusters where targeted interventions are essential to block local transmission. These results highlight the need for preventive measures against imported malaria and enhanced control measures in areas that remain receptive to malaria reemergence due to susceptible hosts and competent vectors.

    Funding:

    This research was funded by the National Institutes of Health, grants R01AI121558, R01AI137395, R01AI155730, F30AI143172, and K24AI134990. Funding was also contributed from the Swedish Research Council, Erling-Persson Family Foundation, and the Yang Fund. RV acknowledges funding from the MRC Centre for Global Infectious Disease Analysis (reference MR/R015600/1), jointly funded by the UK Medical Research Council (MRC) and the UK Foreign, Commonwealth & Development Office (FCDO), under the MRC/FCDO Concordat agreement and is also part of the EDCTP2 program supported by the European Union. RV also acknowledges funding by Community Jameel.